“Linear.ai's AI Auto-Classification saved hours of backlog grooming every single sprint. Tickets get triaged and tagged before our standup even starts.”
Sarah MitchellEngineering Lead at TechFlow
Verified BuyerIntroducing Linear v2.0|Next-gen AI Project Management
Agile, Accelerated by AI.
Linear.ai automatically structures tasks, predicts sprints, and automates backlog grooming so your engineering team can focus on shipping code, not administration.
Core Engine Features
Agile tasks solved instantly.
Stop filling checkboxes manually. Let Linear.ai handle your agile operations autonomously while keeping you in absolute control.
AI Sprint Optimizer
Allocates points, forecasts velocity, and scopes sprint capacities using ML trained on your team's historical execution patterns.
Autonomous Backlog Grooming
Automatically de-duplicates tickets, writes detailed acceptance criteria, and tags dependencies directly from code commits & user chat logs.
PR & Issue Auto-Linking
Fully tracks issues from creation to code merge. AI parses commit messages and PR descriptions to map issues dynamically, keeping status in sync.
Predictive Bottleneck Alerts
Detects scope creep, inactive tasks, and blocker risks before they impact your release schedule. Delivers smart notifications directly to Slack.
Semantic Epic Graph
Generates beautiful visual dependency charts. Helps PMs instantly identify critical paths and technical debt across multiple code repositories.
Voice-to-Ticket Capture
Dictate tasks during standups or video chats. Linear.ai transcribes your updates and constructs fully formed Jira-compatible issues in seconds.
Live Sprint Analytics
Watch your productivity double.
Track backlog progress, automated completions, and real-time developer metrics in a consolidated telemetry cockpit.
Remaining Backlog
AI Task Resolution
Active Sprint Burndown
Live updating graph of the current milestone execution
Sprint Velocity Boost
+18%
Aggressive forecast models yield a significant boost in deliverable commits during each biweekly sprint.
AI Automation Rate
74%
Three out of four issues are automatically generated, structured, and closed via semantic PR linking.
Cycle Time Reduction
-4.2 Days
Tickets flow from backlog triage to staging environments significantly faster by stripping administration.
AI Engine Architecture
How Linear.ai orchestrates projects.
A three-tier pipeline working in the background to keep issues, roadmaps, and dev logs in sync.
Phase 01
Context Ingestion
Linear.ai ingests workspace contexts from Slack conversations, GitHub pull request discussions, Figma design updates, and email streams.
Phase 02
Semantic Synthesis
Our core LLM identifies issue duplicates, maps cross-project technical dependencies, and synthesizes structured tickets with full acceptance criteria.
Phase 03
Predictive Orchestration
Linear.ai scopes tasks dynamically, calculates developer load thresholds, and populates sprints to align automatically with releases.
linear-ai-agent.sh
Slack Ingestion In Progress
#engineering-devs:
"We should probably write a fallback callback URL to handle token expiry errors on the signup page. It currently blocks users."
Author: @sarah_devContext Score: 92%
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Trusted by Agile Teams
Loved by Engineers and Product Leaders
See how autonomous AI workflows are transforming team velocity worldwide.
“The Context-Aware AI Co-Pilot handles project updates effortlessly. It drafts stakeholder summaries from our threads and gets the tone right almost every time.”
David CarterSenior Product Manager
Enterprise Lead“Smart dependency detection catches blockers before they cascade. Our sprint velocity is up and standups are noticeably shorter than before we switched over.”
Emily RodriguezFull-Stack Developer
Agile ManagerFrequently Asked Questions
Got questions? We have answers.
We offer native, one-click API integrations with GitHub, GitLab, Slack, and Figma. Our webhooks capture developer updates, comments, and design specs dynamically to maintain a unified sprint context.
Absolutely. Security is central to our infrastructure. We do not train base models on your code. All metadata is encrypted at rest and in transit, and we are fully SOC2 Type II compliant.
Yes, we support complete migration. Our automated importer lets you bring in history, tickets, sprint logs, epics, and labels from Jira or Linear in less than 5 minutes, without losing context.
Our engine analyzes historical task completion velocity, ticket description patterns, and repository changes to dynamically predict point values, helping teams plan sprints with much higher accuracy.
No. Linear.ai is built to empower them. By automating administrative tasks—like drafting acceptance criteria, linking issues, and running burndown analytics—your team's leaders can focus entirely on design and product vision.
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